Interloom announced it has raised $16.5 million in a seed funding round to address a critical limitation in enterprise AI, the lack of institutional memory. The round was led by DN Capital, with participation from Bek Ventures and Air Street Capital.
The company is building an enterprise operations platform designed to capture expert knowledge and convert it into a persistent memory layer for AI agents. This approach aims to bridge what Interloom describes as a “context gap,” where AI systems struggle to operate effectively due to limited access to real-world operational knowledge.
While AI agents have advanced significantly, many enterprises still face challenges deploying them in practical workflows. A key issue is that most operational knowledge is not formally documented. Interloom estimates that approximately 70% of operational decisions remain undocumented, existing only in emails, tickets, internal communications, or in employees’ experience.
Interloom’s platform captures this knowledge as experts resolve complex cases. These resolutions are then stored and structured into what the company calls a Context Graph, a continuously evolving model of how work is actually performed across an organization. This allows both human employees and AI agents to access prior solutions and apply them to similar problems in the future.
The platform is already being used by enterprises including Zurich Insurance, JLL, and Fiege, where it processes millions of operational cases. By embedding institutional knowledge into AI systems, Interloom enables automation based on real-world experience rather than static documentation.
The company positions its technology as particularly important amid workforce shifts, including the ongoing retirement of experienced employees. With large volumes of institutional knowledge at risk of being lost, Interloom aims to preserve and operationalize that expertise for future use.
Interloom’s system integrates expert oversight with AI-driven automation, ensuring that each resolved case contributes to a growing knowledge base. Over time, this creates what the company describes as a “forever memory” that improves operational efficiency and decision-making.
KEY QUOTES:
“Our experience with enterprise AI agents platforms like Cognigy showed us how important context is. An agent is only as good as the specific knowledge it can rely on. The problem is context is dynamic, poorly documented and lives in the daily decisions of expert front-line workers. Interloom stood out by building a corporate context graph that continuously captures real-world decisions and how organizations actually operate.”
Guy Ward Thomas, Partner, DN Capital
“AI agents are rapidly moving onto the front lines, but without a company’s specific corporate memory, they will not have the answers or the ability to automate anything. We ground their decisions in successful resolutions from the past, ensuring their work is guided by real operational experience and governed through expert oversight, creating a memory that stays with the company forever.”
Fabian Jakobi, Founder & CEO, Interloom
